Overlapping Streptococcus pyogenes and Streptococcus dysgalactiae subspecies equisimilis household transmission and mobile genetic element exchange.

Streptococcus dysgalactiae subspecies equisimilis (SDSE) and Streptococcus pyogenes share skin and throat niches with extensive genomic homology and horizontal gene transfer (HGT) possibly underlying shared disease phenotypes. It is unknown if cross-species transmission interaction occurs. Here, we conduct a genomic analysis of a longitudinal household survey in remote Australian First Nations communities for patterns of cross-species transmission interaction and HGT. Collected from 4547 person-consultations, we analyse 294 SDSE and 315 S. pyogenes genomes. We find SDSE and S. pyogenes transmission intersects extensively among households and show that patterns of co-occurrence and transmission links are consistent with independent transmission without inter-species interference. We identify at least one of three near-identical cross-species mobile genetic elements (MGEs) carrying antimicrobial resistance or streptodornase virulence genes in 55 (19%) SDSE and 23 (7%) S. pyogenes isolates. These findings demonstrate co-circulation of both pathogens and HGT in communities with a high burden of streptococcal disease, supporting a need to integrate SDSE and S. pyogenes surveillance and control efforts.

Inter-species gene flow drives ongoing evolution of Streptococcus pyogenes and Streptococcus dysgalactiae subsp. equisimilis.

Streptococcus dysgalactiae subsp. equisimilis (SDSE) is an emerging cause of human infection with invasive disease incidence and clinical manifestations comparable to the closely related species, Streptococcus pyogenes. Through systematic genomic analyses of 501 disseminated SDSE strains, we demonstrate extensive overlap between the genomes of SDSE and S. pyogenes. More than 75% of core genes are shared between the two species with one third demonstrating evidence of cross-species recombination. Twenty-five percent of mobile genetic element (MGE) clusters and 16 of 55 SDSE MGE insertion regions were shared across species. Assessing potential cross-protection from leading S. pyogenes vaccine candidates on SDSE, 12/34 preclinical vaccine antigen genes were shown to be present in >99% of isolates of both species. Relevant to possible vaccine evasion, six vaccine candidate genes demonstrated evidence of inter-species recombination. These findings demonstrate previously unappreciated levels of genomic overlap between these closely related pathogens with implications for streptococcal pathobiology, disease surveillance and prevention.

Mutational spectra are associated with bacterial niche.

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to detect both disruption of DNA repair processes and exposure to niche-specific mutagens. Here we reconstruct mutational spectra for 84 clades from 31 diverse bacterial species and find distinct mutational patterns. We extract signatures driven by specific DNA repair defects using hypermutator lineages, and further deconvolute the spectra into multiple signatures operating within different clades. We show that these signatures are explained by both bacterial phylogeny and replication niche. By comparing mutational spectra of clades from different environmental and biological locations, we identify niche-associated mutational signatures, and then employ these signatures to infer the predominant replication niches for several clades where this was previously obscure. Our results show that mutational spectra may be associated with sites of bacterial replication when mutagen exposures differ, and can be used in these cases to infer transmission routes for established and emergent human bacterial pathogens.

Accurate and fast graph-based pangenome annotation and clustering with ggCaller.

Bacterial genomes differ in both gene content and sequence mutations, which underlie extensive phenotypic diversity, including variation in susceptibility to antimicrobials or vaccine-induced immunity. To identify and quantify important variants, all genes within a population must be predicted, functionally annotated, and clustered, representing the "pangenome." Despite the volume of genome data available, gene prediction and annotation are currently conducted in isolation on individual genomes, which is computationally inefficient and frequently inconsistent across genomes. Here, we introduce the open-source software graph-gene-caller (ggCaller). ggCaller combines gene prediction, functional annotation, and clustering into a single workflow using population-wide de Bruijn graphs, removing redundancy in gene annotation and resulting in more accurate gene predictions and orthologue clustering. We applied ggCaller to simulated and real-world bacterial data sets containing hundreds or thousands of genomes, comparing it to current state-of-the-art tools. ggCaller has considerable speed-ups with equivalent or greater accuracy, particularly with data sets containing complex sources of error, such as assembly contamination or fragmentation. ggCaller is also an important extension to bacterial genome-wide association studies, enabling querying of annotated graphs for functional analyses. We highlight this application by functionally annotating DNA sequences with significant associations to tetracycline and macrolide resistance in Streptococcus pneumoniae, identifying key resistance determinants that were missed when using only a single reference genome. ggCaller is a novel bacterial genome analysis tool with applications in bacterial evolution and epidemiology.

Mge-cluster: a reference-free approach for typing bacterial plasmids.

Extrachromosomal elements of bacterial cells such as plasmids are notorious for their importance in evolution and adaptation to changing ecology. However, high-resolution population-wide analysis of plasmids has only become accessible recently with the advent of scalable long-read sequencing technology. Current typing methods for the classification of plasmids remain limited in their scope which motivated us to develop a computationally efficient approach to simultaneously recognize novel types and classify plasmids into previously identified groups. Here, we introduce mge-cluster that can easily handle thousands of input sequences which are compressed using a unitig representation in a de Bruijn graph. Our approach offers a faster runtime than existing algorithms, with moderate memory usage, and enables an intuitive visualization, classification and clustering scheme that users can explore interactively within a single framework. Mge-cluster platform for plasmid analysis can be easily distributed and replicated, enabling a consistent labelling of plasmids across past, present, and future sequence collections. We underscore the advantages of our approach by analysing a population-wide plasmid data set obtained from the opportunistic pathogen Escherichia coli, studying the prevalence of the colistin resistance gene mcr-1.1 within the plasmid population, and describing an instance of resistance plasmid transmission within a hospital environment.

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions.

Here we introduce a new endpoint "census population size" to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (MOIvar), based on the hyper-diversity of the var multigene family. We present a Bayesian approach to estimate MOIvar from sequencing and counting the number of unique DBLα tags (or DBLα types) of var genes, and derive from it census population size by summation of MOIvar in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in var diversity, MOIvar, and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, var diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the var population genetic characteristics of a high-transmission system (high var diversity; low var repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Challenges in prokaryote pangenomics.

Horizontal gene transfer (HGT) and the resulting patterns of gene gain and loss are a fundamental part of bacterial evolution. Investigating these patterns can help us to understand the role of selection in the evolution of bacterial pangenomes and how bacteria adapt to a new niche. Predicting the presence or absence of genes can be a highly error-prone process that can confound efforts to understand the dynamics of horizontal gene transfer. This review discusses both the challenges in accurately constructing a pangenome and the potential consequences errors can have on downstream analyses. We hope that by summarizing these issues researchers will be able to avoid potential pitfalls, leading to improved bacterial pangenome analyses.

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe.

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens.

Pneumococcal within-host diversity during colonization, transmission and treatment.

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation.

In less than a decade, population genomics of microbes has progressed from the effort of sequencing dozens of strains to thousands, or even tens of thousands of strains in a single study. There are now hundreds of thousands of genomes available even for a single bacterial species, and the number of genomes is expected to continue to increase at an accelerated pace given the advances in sequencing technology and widespread genomic surveillance initiatives. This explosion of data calls for innovative methods to enable rapid exploration of the structure of a population based on different data modalities, such as multiple sequence alignments, assemblies and estimates of gene content across different genomes. Here, we present Mandrake, an efficient implementation of a dimensional reduction method tailored for the needs of large-scale population genomics. Mandrake is capable of visualizing population structure from millions of whole genomes, and we illustrate its usefulness with several datasets representing major pathogens. Our method is freely available both as an analysis pipeline (https://github.com/johnlees/mandrake) and as a browser-based interactive application (https://gtonkinhill.github.io/mandrake-web/). This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Comparative Genomics of Disease and Carriage Serotype 1 Pneumococci.

The isolation of Streptococcus pneumoniae serotypes in systemic tissues of patients with invasive disease versus the nasopharynx of healthy individuals with asymptomatic carriage varies widely. Some serotypes are hyper-invasive, particularly serotype 1, but the underlying genetics remain poorly understood due to the rarity of carriage isolates, reducing the power of comparison with invasive isolates. Here, we use a well-controlled genome-wide association study to search for genetic variation associated with invasiveness of serotype 1 pneumococci from a serotype 1 endemic setting in Africa. We found no consensus evidence that certain genomic variation is overrepresented among isolates from patients with invasive disease than asymptomatic carriage. Overall, the genomic variation explained negligible phenotypic variability, suggesting a minimal effect on the disease status. Furthermore, changes in lineage distribution were seen with lineages replacing each other over time, highlighting the importance of continued pathogen surveillance. Our findings suggest that the hyper-invasiveness is an intrinsic property of the serotype 1 strains, not specific for a "disease-associated" subpopulation disproportionately harboring unique genomic variation.

Genome-wide association, prediction and heritability in bacteria with application to Streptococcus pneumoniae.

Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for penicillin and ceftriaxone. We show that the MIC traits are highly heritable with high prediction accuracy, explained by many genetic associations under good population structure control. In ceftriaxone MIC, this is surprising because none of the isolates are resistant as per the inhibition zone criteria. We estimate that half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes a quarter of the ceftriaxone MIC heritability. For the within-host carriage duration phenotype, no associations were observed, but the moderate heritability and prediction accuracy indicate a moderately polygenic trait.

Age-specific patterns of DBLα var diversity can explain why residents of high malaria transmission areas remain susceptible to Plasmodium falciparum blood stage infection throughout life.

Immunity to Plasmodium falciparum is non-sterilising, thus individuals residing in malaria-endemic areas are at risk of infection throughout their lifetime. Here we seek to find a genomic epidemiological explanation for why residents of all ages harbour blood stage infections despite lifelong exposure to P. falciparum in areas of high transmission. We do this by exploring, for the first known time, the age-specific patterns of diversity of variant antigen encoding (var) genes in the reservoir of infection. Microscopic and submicroscopic P. falciparum infections were analysed at the end of the wet and dry seasons in 2012-2013 for a cohort of 1541 residents aged from 1 to 91 years in an area characterised by high seasonal malaria transmission in Ghana. By sequencing the near ubiquitous Duffy-binding-like alpha domain (DBLα) that encodes immunogenic domains, we defined var gene diversity in an estimated 1096 genomes detected in sequential wet and dry season sampling of this cohort. Unprecedented var (DBLα) diversity was observed in all ages with 42,399 unique var types detected. There was a high degree of maintenance of types between seasons (>40% seen more than once), with many of the same types, especially upsA, appearing multiple times in isolates from different individuals. Children and adolescents were found to be significant reservoirs of var DBLα diversity compared with adults. Var repertoires within individuals were highly variable, with children having more related var repertoires compared to adolescents and adults. Individuals of all ages harboured multiple genomes with var repertoires unrelated to those infecting other hosts. High turnover of parasites with diverse isolate var repertoires was also observed in all ages. These age-specific patterns are best explained by variant-specific immune selection. The observed level of var diversity for the population was then used to simulate the development of variant-specific immunity to the diverse var types under conservative assumptions. Simulations showed that the extent of observed var diversity with limited repertoire relatedness was sufficient to explain why adolescents and adults in this community remain susceptible to blood stage infection, even with multiple genomes.

An accurate method for identifying recent recombinants from unaligned sequences.

MOTIVATION: Recombination is a fundamental process in molecular evolution, and the identification of recombinant sequences is thus of major interest. However, current methods for detecting recombinants are primarily designed for aligned sequences. Thus, they struggle with analyses of highly diverse genes, such as the var genes of the malaria parasite Plasmodium falciparum, which are known to diversify primarily through recombination. RESULTS: We introduce an algorithm to detect recent recombinant sequences from a dataset without a full multiple alignment. Our algorithm can handle thousands of gene-length sequences without the need for a reference panel. We demonstrate the accuracy of our algorithm through extensive numerical simulations; in particular, it maintains its effectiveness in the presence of insertions and deletions. We apply our algorithm to a dataset of 17 335 DBLα types in var genes from Ghana, observing that sequences belonging to the same ups group or domain subclass recombine amongst themselves more frequently, and that non-recombinant DBLα types are more conserved than recombinant ones. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/qianfeng2/detREC_program. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identifying Targets of Protective Antibodies against Severe Malaria in Papua, Indonesia, Using Locally Expressed Domains of Plasmodium falciparum Erythrocyte Membrane Protein 1.

Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), a diverse family of multidomain proteins expressed on the surface of malaria-infected erythrocytes, is an important target of protective immunity against malaria. Our group recently studied transcription of the var genes encoding PfEMP1 in individuals from Papua, Indonesia, with severe or uncomplicated malaria. We cloned and expressed domains from 32 PfEMP1s, including 22 that were upregulated in severe malaria and 10 that were upregulated in uncomplicated malaria, using a wheat germ cell-free expression system. We used Luminex technology to measure IgG antibodies to these 32 domains and control proteins in 63 individuals (11 children). At presentation to hospital, levels of antibodies to PfEMP1 domains were either higher in uncomplicated malaria or were not significantly different between groups. Using principal component analysis, antibodies to 3 of 32 domains were highly discriminatory between groups. These included two domains upregulated in severe malaria, a DBLß13 domain and a CIDRα1.6 domain (which has been previously implicated in severe malaria pathogenesis), and a DBLδ domain that was upregulated in uncomplicated malaria. Antibody to control non-PfEMP1 antigens did not differ with disease severity. Antibodies to PfEMP1 domains differ with malaria severity. Lack of antibodies to locally expressed PfEMP1 types, including both domains previously associated with severe malaria and newly identified targets, may in part explain malaria severity in Papuan adults.

RCandy: an R package for visualizing homologous recombinations in bacterial genomes.

SUMMARY: Homologous recombination is an important evolutionary process in bacteria and other prokaryotes, which increases genomic sequence diversity and can facilitate adaptation. Several methods and tools have been developed to detect genomic regions recently affected by recombination. Exploration and visualization of such recombination events can reveal valuable biological insights, but it remains challenging. Here, we present RCandy, a platform-independent R package for rapid, simple and flexible visualization of recombination events in bacterial genomes. AVAILABILITY AND IMPLEMENTATION: RCandy is an R package freely available for use under the MIT license. It is platform-independent and has been tested on Windows, Linux and MacOSX. The source code comes together with a detailed vignette available on GitHub at https://github.com/ChrispinChaguza/RCandy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Patterns of within-host genetic diversity in SARS-CoV-2.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The COVID-19 pandemic has had major health impacts across the globe. The scientific community has focused much attention on finding ways to monitor how the virus responsible for the pandemic, SARS-CoV-2, spreads. One option is to perform genetic tests, known as sequencing, on SARS-CoV-2 samples to determine the genetic code of the virus and to find any differences or mutations in the genes between the viral samples. Viruses mutate within their hosts and can develop into variants that are able to more easily transmit between hosts. Genetic sequencing can reveal how genetically similar two SARS-CoV-2 samples are. But tracking how SARS-CoV-2 moves from one person to the next through sequencing can be tricky. Even a sample of SARS-CoV-2 viruses from the same individual can display differences in their genetic material or within-host variants. Could genetic testing of within-host variants shed light on factors driving SARS-CoV-2 to evolve in humans? To get to the bottom of this, Tonkin-Hill, Martincorena et al. probed the genetics of SARS-CoV-2 within-host variants using 1,181 samples. The analyses revealed that 95.1% of samples contained within-host variants. A number of variants occurred frequently in many samples, which were consistent with mutational hotspots in the SARS-CoV-2 genome. In addition, within-host variants displayed mutation patterns that were similar to patterns found between infected individuals. The shared within-host variants between samples can help to reconstruct transmission chains. However, the observed mutational hotspots and the detection of multiple strains within an individual can make this challenging. These findings could be used to help predict how SARS-CoV-2 evolves in response to interventions such as vaccines. They also suggest that caution is needed when using information on within-host variants to determine transmission between individuals.

Common virulence gene expression in adult first-time infected malaria patients and severe cases.

Sequestration of Plasmodium falciparum(P. falciparum)-infected erythrocytes to host endothelium through the parasite-derived P. falciparum erythrocyte membrane protein 1 (PfEMP1) adhesion proteins is central to the development of malaria pathogenesis. PfEMP1 proteins have diversified and expanded to encompass many sequence variants, conferring each parasite a similar array of human endothelial receptor-binding phenotypes. Here, we analyzed RNA-seq profiles of parasites isolated from 32 P. falciparum-infected adult travellers returning to Germany. Patients were categorized into either malaria naive (n = 15) or pre-exposed (n = 17), and into severe (n = 8) or non-severe (n = 24) cases. For differential expression analysis, PfEMP1-encoding var gene transcripts were de novo assembled from RNA-seq data and, in parallel, var-expressed sequence tags were analyzed and used to predict the encoded domain composition of the transcripts. Both approaches showed in concordance that severe malaria was associated with PfEMP1 containing the endothelial protein C receptor (EPCR)-binding CIDRα1 domain, whereas CD36-binding PfEMP1 was linked to non-severe malaria outcomes. First-time infected adults were more likely to develop severe symptoms and tended to be infected for a longer period. Thus, parasites with more pathogenic PfEMP1 variants are more common in patients with a naive immune status, and/or adverse inflammatory host responses to first infections favor the growth of EPCR-binding parasites.

Apparent nosocomial adaptation of Enterococcus faecalis predates the modern hospital era.

Enterococcus faecalis is a commensal and nosocomial pathogen, which is also ubiquitous in animals and insects, representing a classical generalist microorganism. Here, we study E. faecalis isolates ranging from the pre-antibiotic era in 1936 up to 2018, covering a large set of host species including wild birds, mammals, healthy humans, and hospitalised patients. We sequence the bacterial genomes using short- and long-read techniques, and identify multiple extant hospital-associated lineages, with last common ancestors dating back as far as the 19th century. We find a population cohesively connected through homologous recombination, a metabolic flexibility despite a small genome size, and a stable large core genome. Our findings indicate that the apparent hospital adaptations found in hospital-associated E. faecalis lineages likely predate the "modern hospital" era, suggesting selection in another niche, and underlining the generalist nature of this nosocomial pathogen.